Security at Anthropic is not a compliance exercise. It is a core part of how we stay safe as we build increasingly capable systems. Our Responsible Scaling Policy commits us to launching structured security R&D projects: ambitious, time-boxed experiments designed to resolve high-uncertainty questions about our long-term security posture.

Each project runs for roughly 6 months with defined exit criteria. Some will succeed and move toward production. Others will fail, and we'll treat that as useful signals. The questions these projects are designed to answer include:

• Can our core research workflows survive extreme isolation?
• Can we get cryptographic guarantees where we currently rely on trust?
• Can AI become our most effective security control?

As a Security Labs Engineer, you own one or more projects end-to-end: scoping the experiment, building the infrastructure, coordinating across teams, running the pilot, documenting results, and where the experiment succeeds, helping scale it into production. This is 0-to-1 and 1-to-10 work.

Current Project Areas

The portfolio evolves based on what we learn. Current areas include:

• Designing and operating a mock high-assurance research environment: simulating what our infrastructure would look like under extreme isolation and physical security controls, with real measurement of productivity impact
• Exploring cryptographic verification of model integrity using techniques like zero-knowledge proofs to provide mathematical guarantees about what is running in production
• Assessing the feasibility of confidential computing across the full model lifecycle (note: this is an open question, not a committed roadmap item)
• Piloting AI-assisted security tooling including vulnerability discovery, automated patching, anomaly detection, and adaptive behavioral monitoring
• Prototyping API-only access regimes where even internal research workflows never touch raw model weights

Part of your job is helping shape what comes next based on gaps uncovered in the current round.

Responsibilities

• Own the end-to-end execution of a Security Labs project: refine the hypothesis, design the experiment, build the prototype, run the pilot, and write up the results
• Build novel security infrastructure under real time pressure: isolated clusters, hardened access controls, cryptographic verification layers, with a bias toward learning fast
• Where experiments succeed, drive them toward production scale. An experiment that works on one cluster but not a hundred is not a finished result.
• Work embedded with research teams (Pretraining, RL, Inference) to stress-test whether their core workflows can function under extreme security controls, and document precisely where they break
• Evaluate and integrate emerging security technologies through coordination with external vendors and research groups
• Turn experimental results into clear, decision-ready writeups that inform Anthropic's long-term security architecture and RSP commitments
• Maintain a pain-point registry and feasibility assessment for each project, feeding directly into the design of production high-assurance environments
• Help scope and prioritize the next wave of Labs projects based on what the current round uncovers

Requirements

• 7+ years of software or security engineering experience, with a solid foundation in production systems
• Some of that time spent on pilots, prototypes, or applied research work where shipping a working answer to a hard question was the explicit goal
• Strong programming skills in Python and at least one systems language (Go, Rust, or C/C++)
• Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), Kubernetes, and networking fundamentals sufficient to stand up and tear down isolated environments quickly
• A track record of cross-functional execution: you can walk into a room with ML researchers, infrastructure engineers, and vendors and leave with a shared plan
• Clear written communication: you know how to turn six weeks of experimentation into a two-page memo someone can act on
• Comfort with ambiguity and iteration, having run experiments that failed, extracted the lesson, and moved forward
• Genuine curiosity about what it would actually take to defend against a nation-state-level adversary
• Passion for AI safety and a real understanding of the role security plays in making frontier AI development go well
• Bachelor's degree in Computer Science, a related field, or equivalent industry experience required.

Nice to Have

• Prior experience in offensive security, red teaming, or security research, having thought adversarially about systems and knowing which threats actually matter
• Familiarity with airgapped or high-side environments (classified networks, ICS/SCADA, financial trading infrastructure, or similar) and the operational realities of working inside them
• Knowledge of applied cryptography: zero-knowledge proofs, attestation protocols, secure enclaves, TPMs, or confidential computing primitives
• Experience with ML infrastructure (training pipelines, inference serving, model packaging) sufficient for grounded conversations with researchers about what their workflows actually need
• Background building or operating security systems in environments that demand rapid iteration rather than rigid change control
• Prior work at a startup, on an innovation team, or in an applied research group where shipping a working v0 to answer a real question was explicitly the goal

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You won't wait for assignments,you'll identify the highest-leverage problems facing our engineering organisation and own them end-to-end. You'll deliver multi-quarter initiatives that span teams and functions, facilitate tough prioritisation and technical direction decisions, and establish processes that multiply the effectiveness of everyone around you.

This role requires someone who combines technical depth with strategic vision, thrives in ambiguity, and has a proven track record of turning complex, open-ended challenges into executable programs that move the business forward.

We have created the Factors of Growth & Impact to help Villagers better measure impact and articulate coaching, feedback, and the rich and rewarding learning that happens while exploring, developing, and mastering the capabilities and contributions within and outside of the Technical Program Manager role:

Technical Skills:

• Evaluate technical architectures and system designs across teams, identifying risks and trade-offs while ensuring programs are built on sound technical foundations; leverage your engineering background to stay close to implementation details, challenge assumptions, and maintain credibility with senior engineers

• Identify when projects need course correction or are technically infeasible, applying deep technical judgment to influence direction and keep initiatives on track

Complexity and Impact of Work:

• Lead multi-quarter programs spanning multiple teams with area-wide or org-wide impact, establishing clear roadmaps and aligning stakeholders on technical direction and delivery milestones,often under tight deadlines with significant consequences of failure or requiring novel solutions to ambiguous problems

• Proactively identify high-leverage opportunities across the engineering organisation and act on them; facilitate difficult prioritisation decisions and technical tradeoffs, balancing long-term vision with immediate business needs

Organisational Knowledge:

• Maintain a holistic view of engineering and company goals, using judgment to optimise for the wider organisation rather than locally optimal outcomes; anticipate challenges and influence technical direction across teams to execute on your vision, even when facing potential misalignment

• Understand the needs and constraints across engineering and business teams, identifying gaps in capabilities, processes, or tooling and working with partner teams to prioritise their development

Communication and Influence:

• Build deep cross-functional relationships and facilitate the right conversations to reach decisions despite conflicting viewpoints; tailor your message across audiences,from engineers to executives,presenting clearly and concisely at the right level of detail

• Exercise influence without over-leveraging your position; disagree and commit when necessary to move critical priorities forward, creating alignment even in challenging organisational dynamics

You may be a fit for this role if you have:

• 5+ years in technical program management with demonstrated progression into leading large, ambiguous initiatives that span multiple teams and quarters

• Strong software engineering foundation,you've built systems, understand technical architecture, and can engage credibly with senior engineers on implementation details

• Track record of proactively identifying high-impact opportunities, defining the strategy to address them, and driving execution without waiting for direction

• Proven ability to facilitate tough decisions: helping teams reprioritise work, recommending when to end projects that aren't working, or influencing technical approaches when necessary

• Experience introducing org-wide processes or changes, building the business case, and driving adoption across teams

• Demonstrated ability to operate in highly ambiguous environments, defining both the problem and the solution when the path forward is unclear

Although not a requirement, bonus points if:

• Experience in fintech, financial services, or highly regulated environments where compliance and security are critical

• Track record of mentoring or coaching other TPMs or engineers, spreading knowledge through talks, blog posts, or documentation

• Proficiency in scripting or programming (Python, Go, JavaScript) to prototype solutions or build tooling when needed

• You were emotionally moved by the soundtrack to Hamilton, which chronicles the founding of a new financial system. :

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